Enhance Your Site Search Results With These 5 Tips

The digital buying experience typically starts out with a search – on Google or a marketplace like Amazon or on a brand’s website. But regardless of where a customer begins the buying journey, they expect the search function to be easy to use and produce relevant results.  

Many ecommerce sites fall short at meeting these very straightforward and understandable expectations. A study by Baymard found that 42% of ecommerce sites fail to achieve “acceptable ecommerce search UX performance.” Baymard looked at various different query types when evaluating UX performance including exact product names, thematic search queries (e.g., printers, jackets, etc.) and abbreviations/symbols. 

This widespread shortcoming presents a major opportunity for online retailers who can dramatically improve product discovery and boost shopper engagement simply by optimizing their site search functionality. Below, we explore five key strategies to turn your ecommerce site search engine into the effective – and efficient – product search tool that your customers demand.

Tips to Improve Your Site Search Results

In the context of great UX, site search must go beyond simple keyword-matching functionality. It’s a capability that’s baked into how we use the internet and is the starting point to finding information or products or answers when someone goes online. 

From a shopper’s perspective, that translates to relevant and accurate search results, an easy-to-find (and use) search box, and search functionality that works well across devices, channels, and screen sizes.  

Here are five tips that will make your site search results smarter, more intuitive, and incredibly relevant for shoppers:

1. Get AI and ML Involved for More Relevancy

AI and subsets of AI like machine learning and natural language processing (NLP) dramatically improve site search in a few important ways including:

• They enable personalized results: AI uses data and machine learning to personalize search results and improve these results over time. ML algorithms increasingly get better at matching the right products with a specific searcher which means they save shoppers time and the results they produce are more likely to resonate.
• The can decipher search intent: NLP allows the search engine to match results to user intent even when a search query doesn’t exactly match a product name or description in your catalog. For example, someone searching for “fall decor” on a home goods website may get a list of autumnal-themed products (glass pumpkins, felt wreaths, Thanksgiving table decorations, etc.)
• They add semantic enrichment: This feature automatically adds synonyms, adjusts for plurality, and normalizes common attributes like colors and measurements. It helps shoppers find what they’re looking for even if they use different terms than what’s in your product catalog (e.g., a search for “sofa” would also return results for “couch.”)
• They adapt in real-time: ML analyzes in-session behavior like clicks or queries to refine results based on real-time behavioral data. For example, if a shopper clicks on several blue items after searching for “shirts,” the engine might prioritize blue shirts in subsequent searches.
• They prioritize results based on the user: By leveraging historical customer data and current browsing patterns, the search engine can prioritize results based on an individual’s search behavior and preferences. A frequent purchaser of organic products might see those items ranked higher in their search results.

2. Filter and Refine Results with Faceted Search 

Faceted search is a great way to boost ecommerce ROI because it allows shoppers to limit results to specific criteria or product attributes. Facets and filters are valuable when you have a large product catalog (a.k.a., Amazon, Target, etc.). It’s also a boon to mobile searchers because it focuses results on what matters to the searcher versus forcing shoppers to scroll through a bottomless list of products.  

You can set facets to what makes sense for you and your customers – size, product type, color, season, brand, etc. Start by identifying the product attributes and categories that matter most to your customers and incorporate them into your facet strategy. 

3. Make Sure Search is Mobile Ready 

Site search needs to keep mobile shoppers engaged and happy. You’re dealing with much smaller screens and the likelihood of many more distractions including notifications, texts, and calls. Start by making the search bar prominent and easily accessible on every page. 

Features like auto-suggest speed up query input on smaller screens, reduce errors, and make it easy to narrow down the list of products in the search results. Combine this with facets and filters and you’re well on your way to getting the right products in front of customers quickly. You can also use visual elements to enhance UX on mobile. For example, display clear, tappable product images in search results and use a high level of contrast for the search bar. 

4. Personalized Product Recommendations Makes Search Easier

Personalized product recommendations draw from real-time and historical data to display personalized recommendations which can include trending or best-selling items alongside search results. They work by analyzing search patterns, past buying behavior, and in-session behavior to personalize recommendations for each visitor. Advanced NLP makes this approach even more effective since it allows shoppers to search for products even if they don’t know how to spell something or don’t know exactly what they want. 

Relevant suggestions can be presented as a list or bundled into groups (e.g., “Complete the Look” for fashion or “Frequently Bought Together” for categories like technology and home improvement). This may inspire your customers to purchase items they weren’t initially considering and can be an effective way to increase average order value. 

5. Implement Robust Error Handling and “No Results” Strategies

Even the best search engines sometimes fail to produce results, leading to the dreaded “no results” pages or a list of irrelevant products that can be incredibly frustrating for shoppers. To reduce or eliminate the possibility of “no results” pages, a site search best practice is to make sure your site search tool can handle typos and misspellings intelligently. 

In place of a “no results page,” consider displaying related categories, popular products, or search suggestions to keep users engaged. Think of every query as an opportunity to learn about a customer’s needs and preferences. Analyze “no results” searches regularly to identify gaps in your product catalog or potential improvements in your search algorithm.

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